Director of Software Engineering - Content and Experimentation
JPMorgan Chase · Columbus, United States +3 · 1mo ago
Director & ExecutiveOn-siteSoftware Engineering
Our Consumer & Community Banking Group depends on innovators like you to serve consumers, small businesses, municipalities and non-profits. You’ll support the delivery of award winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers.
If you are a software engineering leader ready to take the reins and drive impact, we’ve got an opportunity just for you.
As a Director of Software Engineering at JPMorganChase within the Digital Technology team, you lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.
Job Responsibilities
- Leads technology and process implementations to achieve functional technology objectives
- Accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
- Sets direction and governance for agentic AI-enabled engineering and SDLC/TLM automation within a technical area to drive measurable improvements in speed, quality, and operational outcomes (e.g., AI-orchestrated delivery workflows, release readiness controls, automated test modernization, and incident triage acceleration), while establishing guardrails for validation, security, resiliency, traceability, and reuse across teams
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation and support capacity unlock initiatives at scale
- Carries governance accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations
- Delivers technical solutions that can be leveraged across multiple businesses and domains
- Influences peer leaders and senior stakeholders across the business, product, and technology teams
- Owns the engineering strategy and execution for a Content and Experimentation platform, enabling scalable content delivery, targeting, personalization, and rapid iteration via experimentation
- Partners with Product, Design, Data/Analytics, and Marketing stakeholders to define platform roadmaps, SLAs/SLOs, and measurable outcomes (e.g., experimentation velocity, conversion impact, platform reliability)
- Establishes platform governance for experimentation (guardrails, statistical rigor, auditability, and policy-aligned controls), including standard patterns for feature flags, A/B/n testing, and rollout strategies
- Drives cloud-native delivery on AWS for the platform (e.g., reliability, performance, cost optimization, observability, incident response), with strong focus on secure-by-design and reusable platform capabilities
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- Experience developing or leading cross-functional teams of technologists
- Experience with hiring, developing, and recognizing talent
- Experience leading adoption of agentic AI-enabled engineering practices (using enterprise-authorized tools within the work environment) across teams, including defining operating expectations (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs
- Strong understanding of responsible AI use and control expectations in engineering workflows, including data sensitivity, resiliency/security implications, and governance; ability to influence leaders on safe scaling patterns and reuse
- Practical cloud native experience
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
- Hands-on leadership experience designing and operating content delivery and experimentation capabilities (e.g., feature flags, A/B testing frameworks, rollouts, targeting/personalization) in a multi-team environment
- Strong AWS knowledge for building and running scalable platforms (e.g., networking, compute, storage, security, observability, resiliency patterns, and cost management)
- Experience defining platform operating models (intake, prioritization, self-service enablement, reliability targets, runbooks, and on-call practices) for product-facing engineering platforms
- Strong understanding of API-first and event-driven architectures to integrate content and experimentation services with downstream channels and product applications
Preferred qualifications, capabilities, and skills
- Participate in and lead opportunities with third parties, working to understand why and how we may integrate and leverage their capabilities
- Experience hiring top talent, growing careers, and coaching individuals and managers to higher performance
- Experience operating software platforms
- Strong understanding of AWS services and infrastructure
- Experience with content management platforms (CMS) and content lifecycle concerns (authoring, workflow, governance, localization, versioning, and publishing) to support enterprise-scale content operations